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Research ArticleOpen accessPhrase in the titleThe Development of Community Crime Preventing Network Model in Northeastern ThailandCheuchai Po-Klin, Songkoon Chantachon, Somchai WanluProblem statement: Crime is the thing deteriorating social security. The objectives of this research were to study: (1) the historical background for preventing crime in northeastern region, (2) current situation and problem of community network for preventing crime in northeastern region and (3) develop the model of community network for preventing crime in northeastern region. Approach: The research area included … …Journal of Social Sciences, Vol. 6, Issue 3 · 30 Sep 2010 · 8,178 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleComparative Analysis of Neural Network Models for Predicting EUR/USD Direction: An Empirical StudyEl Badaoui Mohamed, Raouyane Brahim, El Moumen Samira, Bellafkih MostafaThis paper presents a rigorous comparative analysis of six feedforward neural network models for predicting the directional movement of the EUR/USD currency pair. The evaluated models include the Learning Vector Quantization, Cascade Neural Network, Feedforward Neural Network, Single Layer Perceptron, Multi-Layer Perceptron, and Radial Basis Function network. Utilizing daily historical data from April 2009 to May 2024, each model was … …Journal of Computer Science, Vol. 22, Issue 1 · 3 Feb 2026 · 2,330 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleBayesian Regularization in a Neural Network Model to Estimate Lines of Code Using Function PointsK. K. Aggarwal, Yogesh Singh, Pravin Chandra, Manimala PuriIt is a well known fact that at the beginning of any project, the software industry needs to know, how much will it cost to develop and what would be the time required ? . This paper examines the potential of using a neural network model for estimating the lines of code, once the functional requirements are known. Using the … …Journal of Computer Science, Vol. 1, Issue 4 · 31 Dec 2005 · 30,191 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleAn Improved Approach for Detecting Car in Video using Neural Network ModelS. N. Sivanandam, T. Senthil KumarThe study represents a novel approach taken towards car detection, feature extraction and classification in a video. Though many methods have been proposed to deal with individual features of a vehicle, like edge, license plate, corners, no system has been implemented to combine features. Combination of four unique features, namely, color, shape, number plate and logo gives the application a … …Journal of Computer Science, Vol. 8, Issue 10 · 1 Sep 2012 · 7,151 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleQuantization and Pipelined Hardware Implementation of Deep Neural Network ModelsEl Hadrami Cheikh Tourad, Mohsine EleuldjInrecent years, Deep Neural Networks (DNNs) have garnered much interest due toadvances in computational power and data availability. Indeed, DNNs presents a considerable advantage in several challenges, suchas classification problems and video analysis. Although, such accomplishmentleads to significantly increasing energy demands, computational expenses, andmemory capacity. In addition, current efficient DNNs may have more complex andextensive structures. As a result, implementing … …Journal of Computer Science, Vol. 18, Issue 11 · 26 Oct 2022 · 5,703 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleEnhancing Electric Vehicle Charging Demand Prediction Using a Novel SAE-DNN Neural Network Model for Probabilistic ForecastingNaga Raju Hari Manikyam, A. Thangam, J. Murugachandravel et al.The rapid growth and widespread adoption of Electric Vehicles (EVs) play a crucial role in the progress of intelligent transportation systems, resulting in a significant decrease in environmentally damaging greenhouse gas emissions. The increase in EV usage has made it crucial to develop charging infrastructure to keep up with the growing demand. Precisely predicting EV charging demand is crucial to … …Journal of Computer Science, Vol. 21, Issue 10 · 11 Dec 2025 · 3,536 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleA Hybrid Artificial Neural Network Model for Option PricingHanningtone Meshack Simiyu, Anthony Gichuhi Waititu, Jane Aduda AkinyiIn the absence of a well-defined input selection technique associated with the pure ANN models, Option pricing using pure ANN models while relaxing the assumption of constant volatility remains a challenge. The conservative drill espoused has been to make allowances for a large number of input lags with the confidence that the ability of ANN to integrate suppleness and redundancy … …Journal of Mathematics and Statistics, Vol. 15, Issue 1 · 8 Aug 2019 · 7,410 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleComparison of Multiple Linear Regression and Neural Network Models in Bank Performance Prediction in BotswanaHassan Kablay, Victor GumboBank performance is critical to the banking sector and the economy as a whole. In this study, Multiple Linear Regression (MLR) technique and feed forward Neural Network (NN) are used to predict the performance of 11 banks in Botswana. Return on Assets (RoA) is used as the dependent variable, while management quality, credit risk, liquidity, financial leverage and capital adequacy … …Journal of Mathematics and Statistics, Vol. 17, Issue 1 · 10 Jan 2022 · 6,465 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleImage-Based Alzheimer's Disease Detection Using Pretrained Convolutional Neural Network ModelsNasser AlsadhanAlzheimer's disease is an untreatable, progressive brain disorder that slowly robs people of their memory, thinking abilities, and ultimately their capacity to complete even the most basic tasks. Among older adults, it is the most frequent cause of dementia. Although there is presently no treatment for Alzheimer's disease, scientific trials are ongoing to discover drugs to combat the condition. Treatments … …Journal of Computer Science, Vol. 19, Issue 7 · 28 Jun 2023 · 5,909 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleAn Ensemble of Gaussian Mixture Model and Support Vector Machines for Network Intrusion DetectionOlujimi Daniel Alao, Sheriff Alimi, Shade Oluwakemi Kuyoro et al.NetworkIntrusion Detection Systems (NIDS) can protect computer networks and computersystems by detecting abnormal network packets and taking agreed action plans,such as notifying an administrator or rejecting the network packets. In this study,the aim is the implementation of NIDS with improved performance using anensemble of Support Vector Machines (SVMs) and the Gaussian Mixture Model(GMM). Four SVMs with Radial Basis Function (RBF), … …Journal of Computer Science, Vol. 18, Issue 9 · 21 Sep 2022 · 6,114 accessesView PDFCite